Building the architecture of tomorrow. Shipping it this quarter.

Qylogix provides fractional CTO leadership and AI systems architecture for pre-seed through Series B startups. We bridge the gap between experimental R&D and production-grade reality: resolving architectural bottlenecks, controlling inference spend, and building infrastructure your next round can stand on.

Signal Check // Who We Work With

Built for founders from pre-seed through Series B.

You do not need a full-time CTO yet. You need senior technical judgment, applied at the moments where it compounds. You are in the right place if any of these read true:

You're raising. You need a technical leader in the room who has sat on both sides of the diligence table.
Your MVP is winning demos and losing in the field. The prototype proved the idea. Now it needs to survive real users, real data, and real uptime.
Your inference bill is growing faster than revenue. Every user interaction hits a frontier API. There is a cheaper architecture, and you know it.
Your AI strategy is a slide, not a system. The board wants a roadmap that survives contact with production. So do your engineers.
System Capabilities // What We Do

Three disciplines. One operating principle: it has to run in production.

01 / Strategic Architecture

Fractional CTO & AI strategy

Executive technical leadership without the full-time hire. Blueprinting the path from early prototype to enterprise-grade system: build-vs-buy decisions, technical hiring, vendor selection, and an investor-grade technical narrative.

>Technical roadmap
>Architecture review
>Hiring & org design
>Board / investor comms
02 / Edge Infrastructure

On-device & local-first AI

Small language models, custom compute, and hybrid architectures that keep latency, cost, and sensitive data close to the metal. The cloud gets called only when the workload earns it.

>SLM selection & benchmarking
>Local-first + cloud escalation
>Fleet deployment (MDM, LTE)
>Inference cost control
03 / Asynchronous Logic

Production agent systems

Persistent AI workflows on hardened, POSIX-compliant infrastructure. We transform fragile generative demos into observable, recoverable systems that operate continuously at scale.

>Agent & workflow architecture
>LLM routing across mixed compute
>Evals & observability
>Reliability engineering
Engagement Models // How Founders Work With Us

Three ways in. Every one starts with a short discovery call.

AI Strategy Sprint

2–4 weeks · Fixed scope

A focused assessment of your architecture, AI roadmap, and infrastructure spend. You get a written blueprint, a prioritized backlog, and a technical story you can defend to your board or your next investor.

Fractional CTO

1–2 days / week · Ongoing

Embedded technical leadership. Architecture ownership, hiring and vendor decisions, engineering mentorship, and a senior operator at the table for board meetings and diligence.

Architecture & Diligence Review

1–2 weeks · Fixed scope

An independent read on a technical stack or an AI claim. For founders preparing to raise, and for investors who need the demo separated from the deliverable.

> Inquiries that include project specs or current bottlenecks get priority response.
Field Notes // Recent Deployments

Proof over promise.

Healthcare AI · Early Stage

Designed a local-first inference architecture with selective cloud escalation for a clinical-environment product. On-device models carry the always-on workload; the cloud is reserved for calls that justify their cost. Result: a hard ceiling on per-device spend and sensitive audio that never has to leave the room.

Compute Infrastructure

Built an LLM routing layer across a heterogeneous GPU fleet, from datacenter-class nodes to consumer cards. Each request is matched to the cheapest endpoint capable of serving it, with embeddings, utility, and frontier tiers separated by design.

Field Deployment

Stood up a managed tablet fleet for a clinical pilot: MDM enrollment, cellular connectivity, and a repeatable deployment runbook a non-technical team can execute without an engineer on site.

> Details generalized to protect client confidentiality. References available on request.
Operator // Who You're Working With

Jason Morris

Founder & Principal

Qylogix is led by a technologist whose career runs from systems administration and enterprise networking through global-scale data infrastructure and AI strategy. Prior roles include Director of AI Strategy at Microsoft, global AI strategy at Equinix, Big Data Solutions Architect at AWS, and enterprise engagements at Databricks.

He knows the founder side of the table too. A former Managing Partner and angel investor at The Batchery, a Berkeley-based startup accelerator that has supported more than 2,500 startups, he helped early-stage teams move from idea to funded company. He continues to serve as an advisor to multiple startups.

Jason is the author of Hands-On Data Science with the Command Line (Packt) and teaches Big Data and AI for Business at the University of Maryland's Robert H. Smith School of Business. He is a United States Air Force veteran.

The through-line: he has built and operated the systems he now advises on, at startup speed and at hyperscale.

Full profile at jasonmorris.co →

Operator History
  • MicrosoftDirector of AI Strategy
  • EquinixGlobal AI Strategy
  • AWSBig Data Solutions Architect
  • DatabricksEnterprise Data Infrastructure
  • The BatcheryFormer Managing Partner, Startup Accelerator
  • Packt PublishingAuthor, Hands-On Data Science with the Command Line
  • UMD Smith School of BusinessAdjunct Professor, Big Data & AI
  • United States Air ForceVeteran
Comms // Initialize Connection

Reach out.

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The fastest way to connect is direct transmission. Tell us where you are, what you're building, and where the architecture hurts. Serious inquiries with specs get a same-week response.

Node Location Boston, MA
Status Accepting engagements